Show HN: We're pitting 9 AI models in a stock portfolio competition
portfoliogenius.aiHey HN,
I built Portfolio Genius, a platform where AI models manage investment portfolios and compete on public leaderboards.
The experiment:
On Dec 17, 2025, we gave 9 AI models (GPT-5.1, GPT-5.2, Gemini 2.5 Pro, Gemini 3 Pro, Gemini 3 Flash, Claude Opus 4.5, Claude Haiku 3.5, Claude Haiku 4.5, Grok 4) each $10K to manage across three risk profiles: aggressive, moderate, and conservative. That's 27 portfolios total.
The models analyze market conditions, recommend trades, and execute them. Real pricing, real results, updated daily.
Interesting early finding:
For aggressive portfolios, older models are outperforming newer ones:
- GPT-5.1: +5.82% (1st place)
- Gemini 2.5 Pro: +4.94% (2nd)
- Haiku 3.5: +1.80% (3rd)
- Opus 4.5: +1.25% (7th)
My hypothesis: newer models are more "careful" - they hedge, qualify, and second-guess. For aggressive investing, you need conviction. Sometimes being less sophisticated means making bolder calls.
For moderate/conservative portfolios, the pattern is different - newer models do better where nuance matters.
Tech stack:
- Next.js frontend
- Firebase/Firestore backend
- Python Cloud Functions for AI orchestration
- Real-time market data for pricing
- Each model gets the same market data and prompts
What I'm curious about:
- Will the "dumber = bolder" pattern hold over time?
- How will different models react to the same market events?
- Do AI models have investable "personalities"?
Leaderboards: https://portfoliogenius.ai/leaderboards
Would love feedback from the HN community. Happy to answer questions about the architecture or methodology. It would be interesting to also report Alpha and Beta for the portfolios. Absolute returns are great but don’t tell the whole story. Perhaps also average holding duration.